In mathematics, the term optimization refers to the study of problems in which one seeks to minimize or maximize a real function by systematically choosing the values of real or integer variables from within an allowed set. A resulting formulation is called an optimization problem or a mathematical programming problem. Many real world and theoretical problems may be modeled in this general framework. Problems formulated using this technique in the fields of physics and computers may refer to the technique as energy minimization.
The branch of applied mathematics and numerical analysis that is concerned with the development of deterministic algorithms that are capable of guaranteeing convergence in finite time to the actual optimal solution of a non-convex problem is generally labeled optimization.
In particular, the steepest descent method is a generic optimization algorithm that optimizes the system input step by step using the gradient of the cost function. As with all such optimizations, of critical importance are issues relating to speed, accuracy, and automation.